Contrairement à Facebook, qui a vu sa crédibilité s’effondrer, Google a gagné la confiance en proposant une navigation similaire au sherpa à travers des domaines numériques et physiques. Cela lui promet d’énormes bénéfices dans un monde dirigé par l’IA.
Source de l’article sur ZDNet
Dans sa dernière publicité, Samsung s’en prend de nouveau à son meilleur ennemi : Apple. Le fabricant tourne en dérision la lenteur de l’iPhone 6, pour vanter la rapidité de son Galaxy S9. Un peu facile ?
Source de l’article sur ZDNet
La filiale de Google relance une offensive dans le streaming musical mais la lutte sera compliquée face à Apple Music et surtout Spotify.
Source de l’article sur ZDNet
L’Icann a publié la semaine dernière un document temporaire visant à clarifier la position de l’autorité de régulation à l’égard du service WHOIS et du RGPD. Les dispositions prévues par ce texte transitoire devront être implémentées par les bureaux d’enregistrement avant le 25 mai.
Source de l’article sur ZDNet
Les données publiques, les acteurs privés en consomment. Mais les mêmes sont-ils prêts à ouvrir et échanger leurs propres données pour se transformer et résister à la concurrence existante ou à venir ? Outre de les aider, l’Etat pourrait aussi en partie les contraindre.
Source de l’article sur ZDNet
Facebook publie un premier rapport de transparence s’attardant sur la modération des contenus mise en place sur sa plateforme. Il y a quelques semaines, Facebook avait publié ses règles internes de modération.
Source de l’article sur ZDNet
Facebook annonce avoir supprimé plus de 200 applications qui auraient eu un accès trop large aux données personnelles des utilisateurs. Une application s’est ainsi fait épingler pour avoir exposé les données de 3 millions d’Américains.
Source de l’article sur ZDNet
Agree, and focus more on discovery since in *delivery* you have 4 problems: 1. Requirements will change, 2. Requirements are never complete 3. It’s impossible to gather all requirements in beginning 4. You don’t have enough time or $$$ to do everything
This quote is typically the basis of proposing agile software development over traditional software development. While there is some truth in the principles stated there, there is a fundamental flaw.
If the development work has no deadline, no not to exceed budget, no Minimal Viable Capabilities in the sense of MVP’s meaning without these Capabilities being there Features we cannot Go Live on the needed date for the needed budget, then the phrases in the quote may be applicable.
But if the development work is a Project is a fixed period of performance (with margin), for a fixed (with margin) budget, and a fixed set of Capabilities, then the question is can agile be used to develop the software?
The answer is, of course, it can and it is done every single day in many domains I work in. Ranging from embedded flight control systems for winged vehicles to orbiting spacecraft, to Software Intensive System of Systems from industrial, business, insurance, and financial systems.
But these developments are not Products in the sense of the term used by agilest. They are projects in the sense of the term defined by PMI
A project is a temporary endeavor undertaken to create a unique product, service or result. A project is temporary in that it has a defined beginning and end in time, and therefore defined scope and resources.
When an agile advocate says, software development is a product, not a project, and provides all the reasons why the thought process needs to switch from project to products, they may be unfamiliar with how many businesses actually work. In the product development world, the funding, recording of revenue, management of staffing at the financial level is managed as a Project. FASB 86 is an example of how cost and revenue for internal software development are recorded on the balance sheet.
Financial Accounting Standards Board (FASB) Statement No. 86, Accounting for the Costs of Computer Software to Be Sold, Leased, or Otherwise Marketed, applies to the costs of both internally developed and produced software and purchased software to be sold, leased, or otherwise marketed.
Projects build Products on the Balance Sheet. Developers may be working on a Product, but the CFO is recording the work as a Project that has a bounded period of performance, a bounded budget, a bounded set of Capabilities, from which revenue will be generated.
So those loud voices shouting software is product development, may very well hold that view from their position in the firm. But for those signing the paychecks, that is not likely the view.
What Does This Mean for Agile?
Agile shouldn’t care. Agile produces useful working software at the end of every Sprint. If that software is not put into the hands of those paying for the software until some release date, those writing the software shouldn’t care. The software is still useful. It’s likely useful to the Staging and Pre-Production manager. The software is ready for use by someone internal or external to the firm, but regardless of the end uses location the software is still ready for use.
To separate project from the product is a developers point of view, it is not a business point of view.
When you hear that they are separate, and we need to move to a product point of view, you’re likely talking to a coder, that hasn’t taken that Managerial Finance class in his educational institution. For us in the Finance and Business Operations side of writing software for money, it’s a moot point.
Go write code that every few weeks produces value to the next step in the process. That next step could be the end user in some distant land, or it could be the Systems Integration Testing staff down the hall, who in turn produce useful outcomes to the User Acceptance Testing staff across campus, who in turn releases the working UAT code to the customer around the world.
If the agile development team of 6 people sitting in the same room with their end customet who will start using the working software every few weeks for their business, there is no differenc in principle from the team of 6 people who have never met their customer except through the Product Owner who comes from downtown every 3rd day to sit with the team, and who has a go live date for the working system this coming December (7 months from now) and on that date, the customer will have been trained, all the external and internal interfaces to other systems will have been end-to-end verified and validated, and a new system will be avaialbel for those strangers who didn’t even know something new was coming.
So before listening to any conjecture about how agile should be done or not done – establish a context, a domain, a business and technical process, the external and internal business, technical, and financial governance process.
You’re not going live with working software every few weeks for DO-178 flight control system in the same way you can go live every few hours for a sports photo sharing web system. Both ends of the spectrum can and do use agile software development processes. Don’t confuse the business process with the everyday software development processes.
La nouvelle version de l’application revient sur les principaux changements introduits l’hiver dernier. Un constat d’échec pour son patron.
Source de l’article sur ZDNet
There’s a fallacy used by some in the software development business, that estimates are not needed to make decisions in the presence of uncertainty. It turns ourt of course, this can only be true if the world we live in is deterministic.
But we don’t live in a deterministic world, we live in a non-deterministic world. Determinism was debunked long ago. But that determinism was built on a house of sand, the originators of determinism just didn’t know it. In the same way those suggesting we don’t need to estimate, while spending other people’s money is a house built on sand.
Leibniz (1702): “There is no doubt that a man could make a machine which was capable of walking around a town for a time, and of turning precisely at the corners of certain streets. And an incomparably more perfect, although still limited, mind could foresee and avoid an incomparably greater number of obstacles. And this being so, if this world were, as some think it is, only a combination of a finite number of atoms which interact in accordance with mechanical laws, it is certain that a finite mind could be sufficiently exalted as to understand and predict with certainty everything that will happen in a given period. This mind could then not only make a ship capable of getting itself to a certain port, by first giving it the route, the direction, and the requisite equipment, but it could also build a body capable of simulating a man.”
Of course, Laplace had on math to support his position, that came later in the form of differential equations. But Laplace’s statements are the foundation of classical mechanics.
For each system in classical mechanics, there are equations of motions of the form:
d2r / dt2 = F(r)
which have a unique solution for given initial conditions:
(r(t0) = r0 and dr/dt (t0) = v0
Before moving on, the phrase about a machine capable of walking around town has come to pass. So now what about determinism and the machine.
Of course, the machine in the video wouldn’t be able to take a step without falling if it didn’t have a probabilistic feedforward adaptive closed loop control system. Closed-loop control systems actively control the system based on state feedback. Open-loop control systems execute a fixed sequence of control inputs without any feedback. Here’s a nice paper as an example of control systems, « A Probabilistic Approach to Mixed Open-loop and Closed-loop Control, with Application to Extreme Autonomous Driving. »
Putting this to work on Projects
In our domain, the role I usually participate in is called Program Planning and Controls. These planning and controls activities always take place in the presence of uncertainty, which of course creates risk. The presence of uncertainty makes the system indeterminate. And of course to manage in the presence of uncertainty and the resulting risks we need specific processes and practices based on principles.
Since all project work operates in the presence of uncertainty – reducible and irreducible – and the managers of these projects need to make decisions in the presence of these uncertainties, we need to make estimates to inform our decision-making process.
Here’s an example of the probability distribution of a cost estimate for a project.
The 50th percentile cost is $2,296,898. That means there is a 50/50 chance the project will cost more than that or less than that. That number is the median – the middle of the range. If we want to know what the number is with an 80% confidence than it is $2,333,153. That says there is an 80% confidence that the cost of the project will be $2.3M or less.
When we speak about the schedule, we can use the same terminology. In this case, there is an 80% confidence the project will complete on or before 11/06/2015.
These graphs are generated from a Monte Carlo simulation tool applied to a resource loaded Integrated Master Schedule (IMS). If there is any doubt as to why you MUST create a resource loaded schedule, please please put those doubts away. These two graphs are the source for the Joint Confidence Level showing the overall probability distributions for both cost and schedule for the project.
This picture should convince anyone that the « joint » probability of completing on or before the target date (I didn’t say what that was) and at or below that planned budget (didn’t say what that was either) needs to be modeled in a way that would be considered credible.
Outside of a small domain of trained and experienced risk analyst, this is rarely if ever done. Most IT projects have some made up budget and schedule. Their strategy is based almost entirely on HOPE with no underlying assessment of the statistical and probabilistic drivers of the cost and schedule, let alone the technical aspects coupled with risk.
And we wonder why IT projects come in late and over budget
Turns out of course large IT programs have the same problem – poor estimating, politically motivated estimating, naive estimating, etc. But they are required to produce data like this, so we know it is bogus sometimes early enough to fix it – sometimes not.
We only wish it were as simple as many would have us believe. But sadly it is one of those wicked problems that we simply have to manage in the presence of uncertainty.
But no credible decision can be made in the presence of uncertainty without making an estimate of the outcome of that decision.
